Quality of service (QoS) after handoff for networks with Internet Protocol (IP) based backbones has been receiving increased interest in the networking research community. IP networks were originally not designed to provide QoS support and this handicap is even more significant for mobile networks. Real-time applications such as voice over IP (VoIP) are particularly sensitive to QoS and have stringent QoS requirements. Therefore, it is important to ensure adequate performance on such metrics as latency, packet loss, packet jitter and that an adequate amount of bandwidth are provided after handoff.
Existing core network QoS probing tools can be divided into two categories: passive and active probing techniques. Passive QoS estimation techniques generally consist of techniques that collect IP packets on one or more links and record IP, TCP/UDP, or application-layer traces. These use existing traffic on the network and do not inject additional probing packets into the network. The passive monitoring approach has the advantage of not injecting additional probing traffic into the network. It observes the network as it is, meaning that the measurements are an assessment of true network behavior, since this latter is not disturbed by probing traffic intended for those measurements.
The monitoring can take different levels of granularity depending on the degree of processing, storage and resources available. Packet monitoring allows observation of packet-by-packet information such as packet delay variation, packet size distribution, and throughput between host pairs. Higher-level measurements, with less overhead, can be achieved by flow level measurements that record the total number of bytes transferred, the flow start and finish time, among others.
As previously set forth, the main advantage of passive probing techniques is that they do not introduce a load on the network they monitor, which also means they do not distort the network traffic and therefore produce realistic estimates. However their handicap is that they rely on existing traffic, which is not guaranteed to have desired characteristics for certain measurements. For example, bottleneck bandwidth passive measurement techniques require a certain packet size distribution and inter-packet departure rate often not met, which is the case for VoIP traffic. As it relates to the present invention, traffic is not guaranteed to exist through base station candidates at handoff time to the desired correspondent destination and as such relying on passive monitoring is therefore inappropriate.
Active QoS estimation consist of techniques that actively inject measurement traffic into the network and compute metrics based on the received traffic at the receiver or the sender (round-trip or sender response). Active monitoring allows shaping the measurement traffic to approximate user experience as much as possible. The disadvantage of active monitoring is that it sometimes adds a significant overhead to the network in terms of traffic and processing, which may also lead to a distortion of the estimates of network behavior. Active monitoring techniques can be generally categorized into two groups: Internet Control Message Protocol (ICMP) based and packet pair/train approaches.
The underlying concept used in the ICMP-based approach is that a packet sent with a time-to-live (TTL) equal to n will cause router n on the path to identify itself since it will send back an ICMP_time_exceeded message to the sender. A tool referred to as Pathchar is one of the earliest tools based on this technique. For each TTL number, Pathchar sends packets with varying sizes and observes their one-way delay (half the observed round trip time). By successively increasing the TTL, successive hops on the path are unraveled and recursive subtractions of delays allow link-by-link QoS inference for delay, packet loss, bandwidth and queue time.
The problem with Pathchar is the large amount of overhead it requires. For example, 10 MB of data are required to measure a 10-hop Ethernet path bandwidth. This approach is overkill for the purpose of the present invention since QoS estimation is required to occur through several base stations for the handoff of each wireless terminal. As such, the Pathchar tool does not provide an optimal method of providing a QoS aware handoff trigger for VoIP applications.
As set forth above, the other active monitoring technique is the packet-pair/train approach. Its main purpose is to obtain the bottleneck bandwidth, which is the link with the lowest transmission rate. This approach consists of sending two packets or packet trains (several packets) through the path and inferring bottleneck bandwidth from packet inter-arrival times. In this approach the following underlying assumptions are made: 1) the first packet does not experience queuing; and 2) following packets queue one after another at the bottleneck link and at no other subsequent link.
If the assumptions are satisfied, packet inter-arrival times will be proportional to the transmission rate of the bottleneck. Cross traffic can cause the assumptions to be violated by causing undesirable queuing or preventing probe packets from queuing after each other at the bottleneck. Filtering techniques have been proposed to work around distortions in measurements due to cross-traffic.
Voice applications will continue to be a major service of interest among wireless subscribers in future generation networks and as such, a primary concern among wireless communication providers is to define techniques capable of supporting QoS requirements upon handoff time. As such, a need exists for providing QoS to an IP-based core network that assesses QoS performance through a fixed core network hop. In addition, a need exists for a method of combining the result with wireless hop signal power and signal-to-noise ratio (SNR) figures to assess the QoS on the end-to-end path.